from keras.layers import Dense, Activation
from keras.models import Sequential
from keras.layers.core import Flatten
from keras.optimizers import SGD
from keras.layers import Lambda
from keras.layers import Concatenate
from keras.layers import Input, Dense
from keras.models import Model
from keras.layers import SeparableConv2D
from keras.layers import Conv1D
from keras.layers import Conv2D
from keras.layers import MaxPooling2D
from keras.layers import AveragePooling2D
from keras.layers import Activation
from keras.layers import BatchNormalization
from keras.layers import Reshape, Convolution2D
from keras.layers.core import Flatten
from keras import backend as K

model = Sequential()
model.add(Convolution2D(64, 3, 3,
            border_mode='same',
            input_shape=(3, 32, 32)))
model.add(Flatten())
model.add(Dense(units=4))


model.compile(loss='categorical_crossentropy', optimizer=SGD(lr=0.01, momentum=0.9, nesterov=True))
a = 1